Les premiers résultats en analyse convexe ne nécessitant aucune condition de qualification datent à peu près d'une quinzaine d'années et constituent le début de l'analyse convexe séquentielle. Ils concernaient essentiellement: la somme d'un nombre fini de fonctions convexes, la composition avec une application vectorielle convexe, et les problèmes de programmation mathématique convexe. Cette thèse apporte un ensemble de contributions à l'analyse convexe séquentielle. La première partie de la thèse est consacrée à l'obtention sans condition de qualification de règles de calcul sous-differentiel exprimées séquentiellement. On considère les cas suivants:l'enveloppe supérieure d'une famille quelconque de fonctions convexes semi-continues inférieurement définies sur un espace de Banach; une fonctionnelle intégrale convexe générale définie sur un espace de fonctions intégrales;la somme continue (ou intégrale) de fonctions convexes semi-continues inférieurement définies sur un espace de Banach séparable. Dans la deuxième partie on établit sans hypothèse de qualification sur les données du problème, des conditions nécessaires et suffisantes d'optimalité séquentielle pour divers types de problèmes d'optimisation et de contrôle optimal discret ou continu. / The first results in convex analysis without any qualificationcondition have been established fifteen years ago, and one may say thatsequential convex analysis began with those results. They essentially concerned:The finite sum of convex functions, the composition with a vectorvaluedconvex mapping, and convex mathematical programming. The firstpart of this dissertation provides several contibutions to sequential convexanalysis. The following cases are considered: the upper envelop of a familyof lower semicontinuous convex functions; the integral functional overan integral space; the continuous sum of lower semicontinuous convex functions.In the second part, necessary and sufficient optimality conditions areestablished in sequential form for many types of programming problems anddicrete or continuous optimal control problems.

Physics in the year 2006 is tightly constrained by experiment, observation, and mathematical consistency. The Standard Model provides a remarkably precise de- scription of particle physics, and general relativity is quite successful in describing gravitational phenomena. At the same time, it is clear that a more fundamental theory is needed for several distinct reasons. Here we consider a new approach, which begins with the unusually ambitious point of view that a truly fundamental theory should aspire to explaining the origins of Lorentz invariance, gravity, gauge fields and their symmetry, supersymmetry, fermionic fields, bosonic fields, quantum mechanics and spacetime. The present dissertation is organized so that it starts with the most conventional ideas for extending the Standard Model and ends with a microscopic statistical picture, which is actually the logical starting point of the theory, but which is also the most remote excursion from conventional physics. One motivation for the present work is the fact that a Euclidean path integral in quantum physics is equivalent to a partition function in statistical physics. This suggests that the most fundamental description of nature may be statistical. This dissertation may be regarded as an attempt to see how far one can go with this premise in explaining the observed phenomena, starting with the simplest statistical picture imaginable. It may be that nature is richer than the model assumed here, but the present results are quite suggestive, because, with a set of assumptions that are not unreasonable, one recovers the phenomena listed above. At the end, the present theory leads back to conventional physics, except that Lorentz invariance and supersymmetry are violated at extremely high energy. To be more specific, one obtains local Lorentz invariance (at low energy compared to the Planck scale), an SO(N) unified gauge theory (with N = 10 as the simplest possibility), supersymmetry of Standard Model fermions and their sfermion partners, and other familiar features of standard physics. Like other attempts at superunification, the present theory involves higher dimensions and topological defects.

Centro Latino-Americano de Física / Os processos estocásticos com ruído branco multiplicativo são objeto de atenção constante em uma grande área da pesquisa científica. A variedade de prescrições possíveis para definir matematicamente estes processos oferece um obstáculo ao desenvolvimento de ferramentas gerais para seu tratamento. Na presente tese, estudamos propriedades de equilíbrio de processos markovianos com ruído branco multiplicativo. Para conseguirmos isto, definimos uma transformação de reversão temporal de tais processos levando em conta que a distribuição estacionária de probabilidade depende da prescrição. Deduzimos um formalismo funcional visando obter o funcional gerador das funções de correlação e resposta de um processo estocástico multiplicativo representado por uma equação de Langevin. Ao representar o processo estocástico neste formalismo (de Grassmann) funcional eludimos a necessidade de fixar uma prescrição particular. Neste contexto, analisamos as propriedades de equilíbrio e estudamos as simetrias ocultas do processo. Mostramos que, usando uma definição apropriada da distribuição de equilíbrio e considerando a transformação de reversão temporal adequada, as propriedades usuais de equilíbrio são satisfeitas para qualquer prescrição. Finalmente, apresentamos uma dedução detalhada da formulação supersimétrica covariante de um processo markoviano com ruído branco multiplicativo e estudamos algumas das relações impostas pelas funções de correlação através das identidades de Ward-Takahashi. / Multiplicativewhite-noise stochastic processes continuously attract the attention of a wide area of scientific research. The variety of prescriptions available to define it difficults the development of general tools for its characterization. In this thesis, we study equilibrium properties of Markovian multiplicative white-noise processes. For this, we define the time reversal transformation for this kind of processes, taking into account that the asymptotic stationary probability distribution depends on the prescription. We deduce a functional formalism to derive a generating functional for correlation and response functions of a multiplicative stochastic process represented by a Langevin equation. Representing the stochastic process in this functional (Grassmann) formalism, we avoid the necessity of fixing a particular prescription. In this framework, we analyze equilibrium properties and study hidden symmetries of the process. We show that, using a careful definition of equilibrium distribution and taking into account the appropriate time reversal transformation, usual equilibrium properties are satisfied for any prescription. Finally, we present a detailed deduction of a covariant supersymmetric formulation of a multiplicativeMarkovian white-noise process and study some of the constraints it imposes on correlation functions using Ward-Takahashi identities.

Centro Latino-Americano de Física / Os processos estocásticos com ruído branco multiplicativo são objeto de atenção constante em uma grande área da pesquisa científica. A variedade de prescrições possíveis para definir matematicamente estes processos oferece um obstáculo ao desenvolvimento de ferramentas gerais para seu tratamento. Na presente tese, estudamos propriedades de equilíbrio de processos markovianos com ruído branco multiplicativo. Para conseguirmos isto, definimos uma transformação de reversão temporal de tais processos levando em conta que a distribuição estacionária de probabilidade depende da prescrição. Deduzimos um formalismo funcional visando obter o funcional gerador das funções de correlação e resposta de um processo estocástico multiplicativo representado por uma equação de Langevin. Ao representar o processo estocástico neste formalismo (de Grassmann) funcional eludimos a necessidade de fixar uma prescrição particular. Neste contexto, analisamos as propriedades de equilíbrio e estudamos as simetrias ocultas do processo. Mostramos que, usando uma definição apropriada da distribuição de equilíbrio e considerando a transformação de reversão temporal adequada, as propriedades usuais de equilíbrio são satisfeitas para qualquer prescrição. Finalmente, apresentamos uma dedução detalhada da formulação supersimétrica covariante de um processo markoviano com ruído branco multiplicativo e estudamos algumas das relações impostas pelas funções de correlação através das identidades de Ward-Takahashi. / Multiplicativewhite-noise stochastic processes continuously attract the attention of a wide area of scientific research. The variety of prescriptions available to define it difficults the development of general tools for its characterization. In this thesis, we study equilibrium properties of Markovian multiplicative white-noise processes. For this, we define the time reversal transformation for this kind of processes, taking into account that the asymptotic stationary probability distribution depends on the prescription. We deduce a functional formalism to derive a generating functional for correlation and response functions of a multiplicative stochastic process represented by a Langevin equation. Representing the stochastic process in this functional (Grassmann) formalism, we avoid the necessity of fixing a particular prescription. In this framework, we analyze equilibrium properties and study hidden symmetries of the process. We show that, using a careful definition of equilibrium distribution and taking into account the appropriate time reversal transformation, usual equilibrium properties are satisfied for any prescription. Finally, we present a detailed deduction of a covariant supersymmetric formulation of a multiplicativeMarkovian white-noise process and study some of the constraints it imposes on correlation functions using Ward-Takahashi identities.